On the Interplay of Artificial Intelligence and Space-Air-Ground Integrated Networks: A Survey

被引:0
作者
Bakambekova, Adilya [1 ]
Kouzayha, Nour [1 ]
Al-Naffouri, Tareq [1 ]
机构
[1] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal 23955, Saudi Arabia
来源
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY | 2024年 / 5卷
关键词
Artificial intelligence; Surveys; 6G mobile communication; Satellite broadcasting; Wireless networks; Satellites; Resource management; Artificial intelligence (AI); deep learning (DL); high altitude platforms (HAPs); machine learning; reinforcement learning (RL); satellite; space-air-ground integrated network (SAGIN); unmanned aerial vehicle (UAV); NON-TERRESTRIAL NETWORKS; EFFICIENT RESOURCE-ALLOCATION; NONORTHOGONAL MULTIPLE-ACCESS; LEO SATELLITE NETWORKS; ENERGY-EFFICIENT; TRAJECTORY DESIGN; CHANNEL ALLOCATION; WIRELESS NETWORKS; UAV COMMUNICATION; POWER-CONTROL;
D O I
10.1109/OJCOMS.2024.3429198
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial networks with terrestrial wireless systems, are vital enablers of the emerging sixth-generation (6G) wireless networks. They offer significant benefits, including extending high-speed broadband coverage to remote and hard-to-reach areas. However, due to constraints like limited power and storage resources, SAGINs must be intelligently configured and managed to meet their envisioned requirements. Meanwhile, Artificial Intelligence (AI) is another critical enabler of 6G. Due to the recent advancements in AI techniques and hardware capabilities, AI has been leveraged to address the pressing challenges of current and future wireless networks. By adding AI and facilitating the decision-making and prediction procedures, SAGINs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics. In this work, we aim to investigate the interplay of AI and SAGINs by providing a holistic overview of state-of-the-art research in AI-enabled SAGINs. Specifically, we present a comprehensive overview of some potential applications of AI in SAGINs. We also cover open issues in employing AI and detail the contributions of SAGINs in developing AI. Finally, we highlight some limitations of the existing research works and outline potential future research directions.
引用
收藏
页码:4613 / 4673
页数:61
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